Labor and operating room nursing optimization system based on data analysis

Abstract

The present application relates to the field of medical data processing, in particular to a delivery room and operating room nursing optimization system based on data analysis, comprising: collecting maternal and fetal heart rate data and storing in an array; obtaining a fetal heart rate data fluctuation error factor according to the relative size of the maternal and fetal heart rate data; obtaining a fetal heart rate data confidence factor according to the continuous change of the fetal heart rate data fluctuation error factor; obtaining a maternal heart rate data anomaly factor according to the fluctuation of the maternal heart rate belonging to the difference between the previous moment heart rate data value and the difference between all adjacent heart rate data; obtaining a fetal heart rate data anomaly degree parameter by combining the above parameters and factors; continuing to collect heart rate data and updating the array, setting a fetal heart rate anomaly degree parameter threshold to judge whether the fetal heart rate data is abnormal and reminding medical staff to perform nursing, and completing the delivery room and operating room nursing optimization based on data analysis. The present application makes the fetal heart rate anomaly judgment more accurate.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of medical data processing, in particular to a delivery room and operating room nursing optimization system based on data analysis. BACKGROUND

[0002] In the process of delivery room and operating room nursing, continuous monitoring of fetal heart rate has extremely important significance. Continuous monitoring can reflect the changes in fetal heart rate in real time, helping medical staff to assess the health status of the fetus. Through heart rate abnormalities such as too fast, too slow or variability reduction, fetal distress and other problems can be detected early; through timely detection of heart rate abnormalities, fetal hypoxia and other serious complications can be prevented.

[0003] In the existing delivery room and operating room, the fetal or maternal heart rate is prewarned by using a fetal heart monitor to monitor the actual heart rate changes of the fetus, and comparing the actual heart rate changes of the fetus with the general heart rate changes of the fetus to determine whether the fetal heart rate is normal. If the fetal heart rate is abnormal, the fetal heart rate abnormality characteristics are used to guide clinical decision-making (such as intervention timing) to reduce the risk of hypoxia and complications and improve the safety of delivery; but the fetal heart rate and the maternal heart rate may influence each other, such as the physical condition and emotions of the mother affecting the fetal heart rate, and the fetal heart rate may have occasional fluctuations, so it is not accurate enough to judge whether the maternal and fetal heart rates are abnormal according to fixed heart rate change range thresholds, which may lead to normal fetal heart rate changes being misjudged as fetal abnormal heart rate changes and wasting of medical resources, or fetal abnormal heart rate changes being misjudged as fetal normal heart rate changes and missing the best nursing intervention opportunity. SUMMARY

[0004] The present application provides a delivery room and operating room nursing optimization system based on data analysis to solve the existing problem that it is not accurate enough to judge whether the fetal heart rate is abnormal according to fixed fetal and maternal heart rate thresholds.

[0005] The data analysis-based delivery room and operating room nursing optimization method of the present application adopts the following technical solution: In the first aspect of the present application, a data analysis-based delivery room and operating room nursing optimization method is provided, which comprises the following steps: collecting maternal and fetal heart rate data and storing the heart rate data in maternal heart rate arrays and fetal heart rate arrays respectively, obtaining continuous fetal heart rate data and maternal heart rate data; obtaining a fluctuation error factor of each fetal heart rate data according to the relative size of each maternal heart rate data and each fetal heart rate number; obtaining a confidence factor of each fetal heart rate data according to the continuous change of the fluctuation error factor of each fetal heart rate data; obtaining an abnormality factor of each maternal heart rate data according to the difference between the maternal heart rate data value at a certain time and the maternal heart rate data value at the previous time, and the fluctuation of the difference between the maternal heart rate data value at the certain time and the maternal heart rate data value at the previous time; obtaining an abnormality degree parameter of each fetal heart rate data according to the fluctuation error factor of each fetal heart rate data, the confidence factor of each fetal heart rate data, and the abnormality factor of each maternal heart rate data; continuing to collect maternal and fetal heart rate data and updating the arrays, setting a fetal heart rate data abnormality degree parameter threshold, judging whether the collected fetal heart rate data is abnormal according to the abnormality degree parameter threshold, and reminding medical personnel to perform nursing intervention according to the judgment result.

[0006] Further, the collection of maternal and fetal heart rate data and the storage of the heart rate data in maternal heart rate arrays and fetal heart rate arrays respectively, and the obtaining of continuous fetal heart rate data and maternal heart rate data are as follows: A fetal heart monitor and a heart rate monitor are arranged, and the fetal heart monitor and the heart rate monitor are used to collect the heart rates of the fetus and the mother respectively, the collection time interval is P seconds, the collection frequency is B times, and the collected fetal heart rate and maternal heart rate are stored in the fetal heart rate array and the maternal heart rate array respectively according to the collection time sequence, so as to obtain continuous fetal heart rate data and maternal heart rate data.

[0007] Further, the obtaining of the fluctuation error factor of each fetal heart rate data according to the relative size of each maternal heart rate data and each fetal heart rate number is as follows: In the formula, wherein, represents the fluctuation error factor of the u-th fetal heart rate data, represents the u-th fetal heart rate data value, represents the u-th maternal heart rate data value, and B represents the heart rate data collection frequency. represents the i-th fetal heart rate data value, represents the i-th maternal heart rate data value.

[0008] Further, the continuity change of the fluctuation error factor of each fetal heart rate data is used to obtain the confidence factor of each fetal heart rate data, and the specific method is as follows: the fluctuation error factor of the fetal heart rate data is used to fill a preset number set with a length of E, wherein the fluctuation error factor of the last fetal heart rate data in the number set is the fluctuation error factor of the u-th fetal heart rate data, and the confidence factor of the u-th fetal heart rate data is obtained according to the fluctuation error factors of all fetal heart rate data in the number set, and the specific formula is as follows: In the formula, wherein, Fuf represents the confidence factor of the u-th fetal heart rate data, and E represents the length of the number set. wherein, Fuf represents the confidence factor of the u-th fetal heart rate data, and E represents the length of the number set. wherein, Fuf represents the confidence factor of the u-th fetal heart rate data, and E represents the length of the number set. wherein, Fuf represents the confidence factor of the u-th fetal heart rate data, and E represents the length of the number set.

[0009] Further, the difference between the maternal heart rate data value at a certain moment and the maternal heart rate data value at a previous moment, and the fluctuation of the difference between the maternal heart rate data value at the moment and the maternal heart rate data value at a previous moment are used to obtain the abnormal factor of each maternal heart rate data, and the specific method is as follows: In the formula, wherein, Fuf represents the confidence factor of the u-th fetal heart rate data, and E represents the length of the number set. wherein, Fuf represents the confidence factor of the u-th fetal heart rate data, and E represents the length of the number set. wherein, Fuf represents the confidence factor of the u-th fetal heart rate data, and E represents the length of the number set.

[0010] Further, the fluctuation error factor of each fetal heart rate data, the confidence factor of each fetal heart rate data and the abnormal factor of each maternal heart rate data are used to obtain the abnormal degree parameter of each fetal heart rate data, and the specific method is as follows: In the formula, wherein, Fuf represents the confidence factor of the u-th fetal heart rate data, and E represents the length of the number set. wherein, Fuf represents the confidence factor of the u-th fetal heart rate data, and E represents the length of the number set. wherein, Fuf represents the confidence factor of the u-th fetal heart rate data, and E represents the length of the number set. wherein, Fuf represents the confidence factor of the u-th fetal heart rate data, and E represents the length of the number set.

[0011] Further, the method further comprises: continuously collecting the maternal and fetal heart rate data and updating the arrays, setting a fetal heart rate data abnormality degree parameter threshold, judging whether the collected fetal heart rate data is abnormal according to the abnormality degree parameter threshold, and reminding medical staff to perform nursing intervention according to the judgment result, and the specific method is as follows: simultaneously collecting new fetal heart rate and maternal heart rate by using the fetal heart monitor and the heart rate monitor, the collection time interval is P seconds, the collection times is V times, the maternal and fetal data is collected once each time, the fetal heart rate array and the maternal heart rate array are updated, the first element in the fetal heart rate array and the maternal heart rate array is deleted, and all the remaining elements in the array are moved one position forward, finally the newly collected fetal heart rate and maternal heart rate data are added to the end of the two arrays respectively, the fetal heart rate data abnormality degree parameter collected each time is calculated according to the maternal heart rate data and the fetal heart rate data in the new array, and the fetal heart rate data abnormality degree parameter threshold Q is set, the fetal heart rate data abnormality parameter collected each time is compared with the fetal heart rate data abnormality degree parameter threshold Q, if the fetal heart rate data abnormality parameter is greater than the fetal heart rate data abnormality degree parameter threshold Q, the medical staff is reminded to perform intervention nursing.

[0012] In a second aspect of the present application, a delivery room and operating room nursing optimization system based on data analysis is provided, which comprises a temperature acquisition module, a parameter calculation module and a processing warning module, wherein: the heart rate acquisition module is used for collecting maternal and fetal heart rate data and storing the heart rate data into maternal heart rate arrays and fetal heart rate arrays respectively, so as to obtain continuous fetal heart rate data and maternal heart rate data; the parameter calculation module is used for obtaining a fluctuation error factor of each fetal heart rate data according to the relative size of each maternal heart rate data and each fetal heart rate data; obtaining a confidence factor of each fetal heart rate data according to the continuity change of the fluctuation error factor of each fetal heart rate data; obtaining an abnormality factor of each maternal heart rate data according to the difference between the maternal heart rate data value at a certain moment and the maternal heart rate data value at the previous moment, and the fluctuation of the difference between the maternal heart rate data value at the certain moment and all adjacent maternal heart rate data values before the certain moment; obtaining an abnormality degree parameter of each fetal heart rate data according to the fluctuation error factor of each fetal heart rate data, the confidence factor of each fetal heart rate data and the abnormality factor of each maternal heart rate data; and the collection warning module is used for continuously collecting maternal and fetal heart rate data and updating the arrays, setting a fetal heart rate data abnormality degree parameter threshold, judging whether the collected fetal heart rate data is abnormal according to the abnormality degree parameter threshold, and reminding medical staff to perform nursing intervention according to the judgment result.

[0013] In a third aspect of the present application, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program, wherein the computer program is executed by a processor to implement the steps of the above-mentioned delivery room and operating room nursing optimization method based on data analysis.

[0014] In a fourth aspect, the application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor implements the steps of the method for optimizing delivery room and operating room nursing based on data analysis when running the computer program.

[0015] The technical scheme of the application has the beneficial effects that: maternal and fetal heart rate data are collected and stored in maternal heart rate arrays and fetal heart rate arrays respectively, continuous fetal heart rate data and maternal heart rate data are obtained; maternal and fetal heart rate data are collected at the same time, which facilitates synchronous comparison and analysis of abnormal conditions of maternal and fetal heart rate data; a fluctuation error factor of each fetal heart rate data is obtained according to the relative size of each maternal heart rate data and each fetal heart rate data; whether fetal heart rate fluctuation is abnormal is determined according to the fluctuation rule and trend of maternal heart rate, which can to some extent avoid the situation that maternal heart rate is relatively high or low due to maternal emotional changes, which affects fetal heart rate and causes fetal heart rate to be misjudged as an abnormal condition; a confidence factor of each fetal heart rate data is obtained according to the continuity change of the fluctuation error factor of each fetal heart rate data; fetal heart rate may have accidental fluctuation, and abnormal values may appear in some moment data, which may cause the system to misjudge and identify normal heart rate data as abnormal, thereby misleading medical staff to take unnecessary intervention measures and wasting medical resources; an abnormal factor of each maternal heart rate data is obtained according to the difference between the maternal heart rate data value at a moment and the maternal heart rate data value at the previous moment, and the fluctuation condition of the difference between the maternal heart rate data value at the moment and all adjacent maternal heart rate data values before the moment; maternal heart rate itself has an abnormal condition, fetal heart rate may also have an abnormal condition, and the abnormality judgment of fetal heart rate at this moment may not be accurate, so the step of judging whether the maternal heart rate is abnormal is used, and the higher the abnormality degree of maternal heart rate at a moment, the less accurate the abnormality condition of fetal heart rate at the moment, and the higher the probability that medical staff need to intervene and nurse; an abnormality degree parameter of each fetal heart rate data is obtained according to the fluctuation error factor of each fetal heart rate data, the confidence factor of each fetal heart rate data, and the abnormal factor of each maternal heart rate data; the fetal heart rate abnormality degree is more accurate in combination with the above factors and parameters; maternal and fetal heart rate data are continuously collected and the arrays are updated, a fetal heart rate data abnormality degree parameter threshold is set, whether the collected fetal heart rate data is abnormal is judged according to the abnormality degree parameter threshold, and medical staff are reminded to intervene and nurse according to the judgment result; maternal and fetal heart rate data can be continuously and synchronously collected, and the fetal heart rate abnormality degree can be calculated, the abnormal condition of fetal heart rate can be monitored in real time, and medical staff can be reminded to intervene and nurse in time. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0017] Figure 1 The step flow chart of the labor room and operating room nursing optimization method based on data analysis of the present application; Figure 2 The structural block diagram of the labor room and operating room nursing optimization system based on data analysis of the present application. DETAILED DESCRIPTION

[0018] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined object, the following will combine the drawings and the preferred embodiments to specifically describe the labor room and operating room nursing optimization method based on data analysis according to the present application, its specific implementation, structure, features and effects in detail. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0020] The following will specifically describe the specific scheme of the labor room and operating room nursing optimization method based on data analysis provided by the present application in combination with the drawings.

[0021] Please refer to Figure 1 which shows the step flow chart of the labor room and operating room nursing optimization method based on data analysis of the first object of the present application, and the method comprises the following steps: step S001: collecting maternal and fetal heart rate data and storing the heart rate data into maternal heart rate array and fetal heart rate array respectively, and obtaining continuous fetal heart rate data and maternal heart rate data.

[0022] It should be noted that, since the heart rates of different mothers and fetuses have differences, the heart rate data of the mother and fetus needs to be collected in this step, which is used for comparative analysis of the abnormal state of maternal and fetal heart rate.

[0023] Specifically, the maternal and fetal heart rate data are collected and stored in the maternal heart rate array and the fetal heart rate array, respectively. The specific method for obtaining continuous fetal heart rate data and maternal heart rate data is as follows: a fetal heart monitor and a heart rate monitor are arranged, and the fetal and maternal heart rates are collected by the fetal heart monitor and the heart rate monitor, respectively. The collection time interval is P seconds, the collection times are B times, and the collected fetal heart rate and maternal heart rate are stored in the fetal heart rate array and the maternal heart rate array, respectively, to obtain continuous fetal heart rate data and maternal heart rate data.

[0024] It should be noted that in this embodiment, the time interval P for collecting heart rate is 5 seconds, and the collection times are 1000 times. The time interval for collecting heart rate data and the collection times are not limited in this embodiment, but are determined according to the specific implementation in other embodiments.

[0025] Step S002: obtaining a fluctuation error factor of each heart rate data of the fetus according to the relative size of each heart rate data of the mother and each heart rate data of the fetus; obtaining a confidence factor of each heart rate data of the fetus according to the continuous change of the fluctuation error factor of each heart rate data of the fetus; obtaining an abnormality factor of each heart rate data of the mother according to the difference between the value of the maternal heart rate data at a certain time and the value of the maternal heart rate data at the previous time, and the fluctuation of the difference between the value of the maternal heart rate data at the certain time and the value of all adjacent maternal heart rate data; and obtaining an abnormality degree parameter of each heart rate data of the fetus according to the fluctuation error factor of each heart rate data of the fetus, the confidence factor of each heart rate data of the fetus, and the abnormality factor of each heart rate data of the mother.

[0026] It should be noted that the traditional method for determining whether the fetal heart rate is abnormal is to compare the general change range of the fetal heart rate with the actual change range of the fetal heart rate. However, it is not accurate to determine whether the fetal heart rate is abnormal according to the fixed heart rate change range, because the fetal heart rate is affected by the maternal heart rate.

[0027] It should be further noted that this step needs to determine whether the fetal heart rate fluctuation is abnormal according to the fluctuation rule and trend of the maternal heart rate, which can to some extent avoid the fetal heart rate being misjudged as an abnormal situation due to the high or low maternal heart rate caused by the change of the maternal emotion.

[0028] Specifically, the fluctuation error factor of each heart rate data of the fetus is obtained according to the relative size of each heart rate data of the mother and each heart rate data of the fetus, and the specific method is as follows: In the formula, wherein, represents the fluctuation error factor of the u-th heart rate data of the fetus, represents the value of the u-th heart rate data of the fetus, indicates the i-th heart rate data value of the fetus, indicates the i-th heart rate data value of the mother.

[0029] It should be noted that the fluctuation error factor of each heart rate data of the fetus is obtained according to the above method, The closer to the value 1, the greater the difference between the u-th heart rate data value of the fetus and the u-th heart rate data value of the mother, and the closer to the average difference between all fetal heart rate data and maternal heart rate data, the more normal the fetal heart rate data at this time, that is, The smaller, the more normal the u-th heart rate of the fetus, that is, The smaller, the more normal the u-th heart rate of the fetus.

[0030] It should be further noted that the fluctuation error factor of each heart rate data of the fetus is obtained according to the relative size of the fetal heart rate data and the maternal heart rate data, but due to the accidental fluctuation of the fetal heart rate, the data at some time may appear abnormal value, and this accidental fluctuation may lead to system misjudgment, identifying normal heart rate data as abnormal, and further misleading medical personnel to take unnecessary intervention measures, wasting medical resources; The normal or abnormal situation of fetal heart rate is mostly persistent, so if the abnormality degree of the fetal heart rate data at this time is relatively stable, the fetal heart rate data at this time is relatively close to the true situation; Therefore, this step needs to set a number set with a length of E for storing continuous fetal heart rate data values, and the length of the number set in this embodiment is 10, and the length of the number set is not specifically limited in this embodiment, but the length of the number set needs to be less than or equal to the number of collected heart rate data B.

[0031] Specifically, according to the continuous change of the fluctuation error factor of each heart rate data of the fetus, the confidence factor of each heart rate data of the fetus is obtained, and the specific method is as follows: the fluctuation error factor of the fetal heart rate data is used to fill the preset number set with a length of E, wherein the fluctuation error factor of the last fetal heart rate data in the number set is the fluctuation error factor of the u-th heart rate data of the fetus, and the confidence factor of the u-th heart rate data of the fetus is obtained according to the fluctuation error factors of all fetal heart rate data in the number set. The specific formula is as follows: In the formula, indicates the confidence factor of the u-th heart rate data of the fetus, and E indicates the length of the number set, indicates the fluctuation error factor of the j-th heart rate data of the fetus, indicates the mean value of the fluctuation error factors of all fetal heart rate data in the number set with the fluctuation error factor of the j-th heart rate data of the fetus at the end, represents the mean of all the heart rate data fluctuation error factors in the set except the jth heart rate data fluctuation error factor of the fetus, j represents the sequence of the first heart rate data fluctuation error factor of the fetus in the set; when the confidence factor of the u th heart rate data of the fetus is calculated, the set is emptied, and the length of the set remains unchanged.

[0032] It should be noted that the confidence factor of each heart rate data of the fetus is obtained according to the above method, and when The smaller the confidence factor of the u th heart rate data of the fetus is, the closer the deviation of the heart rate data fluctuation error factor at the end of the set from the mean of all the heart rate data fluctuation error factors in the set after removing the heart rate data of the fetus at the end of the set is to the deviation of all the heart rate data fluctuation error factors of the fetus from the mean in the set, and the closer the heart rate data fluctuation error factor at the end of the set is to the general level of the heart rate data fluctuation error factor of the fetus, that is, the smaller the confidence factor of the u th heart rate data of the fetus is, the higher the confidence of the fluctuation error factor of the u th heart rate data of the fetus is, and the lower the probability that the heart rate data misleads medical staff is.

[0033] It should be further noted that the calculation and judgment of the above-mentioned fetal heart rate are based on the joint calculation of the fetal heart rate and the maternal heart rate. If the maternal heart rate itself has an abnormal condition, the fetal heart rate may also have an abnormal condition, and at this time, the abnormal judgment of the fetal heart rate may not be accurate enough, so this step needs to judge whether the maternal heart rate is abnormal. The higher the abnormality degree of the maternal heart rate at a certain moment is, the less accurate the abnormality of the fetal heart rate at that moment is, and the higher the probability that medical staff needs to intervene in nursing is.

[0034] Specifically, according to the difference between the maternal heart rate data value at a certain moment and the maternal heart rate data value at the previous moment, and the fluctuation of the difference between the maternal heart rate data value at that moment and all the adjacent maternal heart rate data values, an abnormal factor of each heart rate data of the maternal is obtained, and the specific method is as follows: In the formula, represents the abnormal factor of the u th heart rate data of the maternal, represents the u th heart rate data value of the maternal, represents the u-1 th heart rate data value of the maternal.

[0035] It should be noted that the abnormal factor of each heart rate data of the maternal is obtained according to the above method, and when The greater the abnormal factor of the u th heart rate data of the maternal is, the more obvious the difference between the u th heart rate data and the u-1 th heart rate data is compared with the difference between all the adjacent heart rate data of the maternal before that, the greater the probability of the abnormality of the u th heart rate data of the maternal is, and the greater the abnormal factor of the u th heart rate data of the maternal is, the greater the probability of the abnormality of the u th heart rate data of the maternal is, and when The closer to 1, the smaller the probability of the abnormality of the u-th heart rate data of the mother.

[0036] It should be further explained that the fluctuation error factor of each heart rate data of the fetus, the confidence factor of each heart rate data of the fetus, and the abnormality factor of each heart rate data of the mother are obtained, and the abnormality degree parameter of each heart rate data of the fetus can be obtained by combining the obtained parameters.

[0037] Specifically, according to the fluctuation error factor of each heart rate data of the fetus, the confidence factor of each heart rate data of the fetus, and the abnormality factor of each heart rate data of the mother, the abnormality degree parameter of each heart rate data of the fetus is obtained by the following specific method: In the formula, indicates the abnormality degree parameter of the u-th heart rate data of the fetus, indicates the fluctuation error factor of the u-th heart rate data of the fetus, indicates the confidence factor of the u-th heart rate data of the fetus, indicates the abnormality factor of the u-th heart rate data of the mother.

[0038] It should be noted that the abnormality degree parameter of each heart rate data of the fetus is obtained according to the above method, and the value 0.01 in the parentheses is to prevent the factors and parameters from being 0, which causes the abnormality degree parameter of the heart rate data of the fetus to be 0. As can be seen from the above, that is, The smaller the value is, the more normal the u-th heart rate of the fetus is; The smaller the value is, the higher the confidence of the fluctuation error factor of the u-th heart rate data of the fetus is; The greater the value is, the greater the probability of the abnormality of the u-th heart rate data of the mother is; therefore, when The greater the value is, The smaller the value is, The smaller the value is, the smaller the abnormality degree parameter of the u-th heart rate data of the fetus is The greater the value is, the higher the probability of the abnormality of the u-th heart rate data of the fetus is, and the higher the data authenticity is, and the greater the probability of nursing intervention by medical staff is.

[0039] Step S003: Continue to collect the heart rate data of the mother and the fetus and update the array, set the abnormality degree parameter threshold of the heart rate data of the fetus, judge whether the collected heart rate data of the fetus is abnormal according to the abnormality degree parameter threshold, and remind the medical staff to perform nursing intervention according to the judgment result.

[0040] It should be noted that the abnormality degree parameter of each heart rate data of the fetus is obtained, and a heart rate data abnormality degree parameter threshold is preset, and the subsequent collected heart rate data of the mother and the fetus is judged.

[0041] The maternal and fetal heart rate data are continuously collected and the arrays are updated, the fetal heart rate data abnormality degree parameter threshold is set, whether the collected fetal heart rate data is abnormal is judged according to the fetal heart rate data abnormality degree parameter threshold, and the medical staff is reminded to perform nursing intervention according to the judgment result, and the specific method is as follows: the fetal heart rate and the maternal heart rate are collected by using the fetal heart monitor and the heart rate monitor at the same time, the collection time interval is P seconds, the collection times are V times, the maternal and fetal data are collected once each time, the fetal heart rate array and the maternal heart rate array are updated, the first element in the fetal heart rate array and the maternal heart rate array is deleted, and all the remaining elements in the array are moved one position forward, finally, the newly collected fetal heart rate and maternal heart rate data are added to the end of the two arrays respectively, the fetal heart rate data abnormality degree parameter collected each time is calculated according to the maternal heart rate data and the fetal heart rate data in the new array, and the fetal heart rate data abnormality degree parameter threshold Q is set, the fetal heart rate data abnormality parameter collected each time is compared with the fetal heart rate data abnormality degree parameter threshold Q, and if the fetal heart rate data abnormality parameter is greater than the fetal heart rate data abnormality degree parameter threshold Q, the medical staff is reminded to perform intervention nursing.

[0042] It should be noted that in this embodiment, the fetal heart rate data abnormality parameter threshold is 0.72, and the fetal heart rate data abnormality parameter threshold is not limited in this embodiment.

[0043] Please refer to Figure 2 which shows the structure block diagram of the delivery room and operating room nursing optimization system based on data analysis, the system comprises the following modules: a heart rate collection module for collecting maternal and fetal heart rate data and storing the heart rate data into a maternal heart rate array and a fetal heart rate array respectively to obtain continuous fetal heart rate data and maternal heart rate data; a parameter calculation module for obtaining a fluctuation error factor of each fetal heart rate data according to the relative size of each maternal heart rate data and each fetal heart rate data; obtaining a confidence factor of each fetal heart rate data according to the continuity change of the fluctuation error factor of each fetal heart rate data; obtaining an abnormality factor of each maternal heart rate data according to the difference between the maternal heart rate data value at a certain moment and the maternal heart rate data value at the previous moment, and the fluctuation of the difference between the maternal heart rate data value at the certain moment and all the adjacent maternal heart rate data values before the certain moment; obtaining an abnormality degree parameter of each fetal heart rate data according to the fluctuation error factor of each fetal heart rate data, the confidence factor of each fetal heart rate data and the abnormality factor of each maternal heart rate data; and a collection early warning module for continuously collecting maternal and fetal heart rate data and updating the arrays, setting the fetal heart rate data abnormality degree parameter threshold, judging whether the collected fetal heart rate data is abnormal according to the fetal heart rate data abnormality degree parameter threshold, and reminding the medical staff to perform nursing intervention according to the judgment result.

[0044] The third object of the embodiments of the present application is to provide a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned data analysis-based labor room and operating room nursing optimization method when executing the computer program.

[0045] The fourth object of the embodiments of the present application is to provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program implements the steps of the above-mentioned data analysis-based labor room and operating room nursing optimization method when executed by a processor.

[0046] The embodiment collects maternal and fetal heart rate data and stores the heart rate data into maternal heart rate array and fetal heart rate array respectively, obtains continuous fetal heart rate data and maternal heart rate data; simultaneously collects fetal and maternal heart rate data, which is convenient for synchronous comparison and analysis of abnormal conditions of maternal and fetal heart rate data; obtains fluctuation error factor of each fetal heart rate data according to relative size of each maternal heart rate data and each fetal heart rate data; judges whether fetal heart rate fluctuation is abnormal according to fluctuation rule and trend of maternal heart rate, which can avoid that maternal heart rate is higher or lower due to maternal emotional change, fetal heart rate is affected and fetal heart rate is misjudged as abnormal condition; obtains confidence factor of each fetal heart rate data according to continuity change of fluctuation error factor of each fetal heart rate data; fetal heart rate may exist accidental fluctuation, abnormal value may appear in some moment data, the accidental fluctuation may lead to system misjudgment, normal heart rate data is identified as abnormal, and medical staff is misled to take unnecessary intervention measures, which wastes medical resources; the step can avoid that medical staff is misled by accidental heart rate data to a certain extent; obtains abnormal factor of each maternal heart rate data according to difference size between maternal heart rate data value at a moment and maternal heart rate data value at a previous moment and fluctuation condition of difference size between all adjacent maternal heart rate data values at the moment; maternal heart rate itself exists abnormal condition, fetal heart rate may also exist abnormal condition, and the abnormal judgment of fetal heart rate at this moment may not be accurate enough; the step judges whether maternal heart rate is abnormal, if the abnormal degree of maternal heart rate at a moment is higher, the abnormal condition of fetal heart rate at the moment is less accurate, and the probability that medical staff needs to intervene and nurse is higher; obtains abnormal degree parameter of each fetal heart rate data according to fluctuation error factor of each fetal heart rate data, confidence factor of each fetal heart rate data and abnormal factor of each maternal heart rate data; the fetal heart rate abnormal degree is more accurate in combination with the above factors and parameters; continues to collect maternal and fetal heart rate data and updates the array, sets fetal heart rate data abnormal degree parameter threshold, judges whether the collected fetal heart rate data is abnormal according to the abnormal degree parameter threshold and reminds medical staff to intervene and nurse according to the judgment result; maternal and fetal heart rate data can be continuously and synchronously collected and fetal heart rate abnormal degree can be calculated, fetal heart rate abnormal condition can be monitored in real time, and medical staff can be reminded to intervene or nurse in time.

[0047] Those skilled in the art will appreciate that embodiments of the application can be supplied as methods, systems, or computer program products. Accordingly, the application can be embodied in the form of complete hardware embodiments, complete software embodiments, or embodiments combining software and hardware aspects. Furthermore, the application can be embodied in the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage media, etc.) having computer usable program code embodied thereon.

[0048] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 means for functionally implementing the steps listed in the flowchart block or blocks.

[0049] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the function specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 means for functionally implementing the steps listed in the flowchart block or blocks.

[0050] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 means for functionally implementing the steps listed in the flowchart block or blocks.

[0051] Finally, it should be noted that the above-mentioned embodiments are merely intended to illustrate the technical solutions of the present application, rather than limit the technical solutions of the present application. Although the present application has been described in detail with reference to the above-mentioned embodiments, those skilled in the art should understand that the specific embodiments of the present application can be modified or replaced equivalently without departing from the spirit and scope of the present application, and any modification or equivalent replacement without departing from the spirit and scope of the present application should be covered in the protection scope of the claims of the present application.

Claims

1. A data-driven nursing optimization system for delivery rooms and operating rooms, characterized in that, The system includes the following modules: a heart rate acquisition module, used to collect maternal and fetal heart rate data and store the heart rate data into maternal heart rate arrays and fetal heart rate arrays respectively, and obtain continuous fetal heart rate data and maternal heart rate data; The parameter calculation module is used to obtain the fluctuation error factor of each fetal heart rate data based on the relative magnitude of each maternal heart rate data and each fetal heart rate data; to obtain the confidence factor of each fetal heart rate data based on the continuous change of the fluctuation error factor of each fetal heart rate data; to obtain the abnormality factor of each maternal heart rate data based on the fluctuation of the difference between the maternal heart rate data value at a certain moment and the previous moment's maternal heart rate data value and the difference between the maternal heart rate data value at that moment and all adjacent maternal heart rate data values ​​before that moment; and to obtain the abnormality degree parameter of each fetal heart rate data based on the fluctuation error factor, the confidence factor, and the abnormality factor of each maternal heart rate data. The data acquisition and early warning module is used to continue collecting maternal and fetal heart rate data and updating the array. It sets a threshold for the degree of fetal heart rate data abnormality, determines whether the collected fetal heart rate data is abnormal based on the threshold, and alerts medical staff to provide nursing intervention based on the judgment result. The confidence factor is obtained as follows: a preset set of data of length E is filled with the fluctuation error factor of the fetal heart rate data, where the fluctuation error factor of the last fetal heart rate data in the set is the fluctuation error factor of the u-th fetal heart rate data. The confidence factor of the u-th fetal heart rate data is obtained based on the fluctuation error factors of all fetal heart rate data in the set, using the following formula: In the formula, This represents the confidence factor for the u-th fetal heart rate data point, where E represents the data set length. This represents the fluctuation error factor of the j-th fetal heart rate data. Let represent the mean of all fetal heart rate data fluctuation error factors in the set where the j-th fetal heart rate data fluctuation error factor ends. The set represents the mean of all heart rate data fluctuation error factors after removing the j-th fetal heart rate data fluctuation error factor from the set ending with the fetal heart rate data fluctuation error factor. Here, j represents the sequence of the first fetal heart rate data fluctuation error factor in the set. After the confidence factor for the u-th fetal heart rate data is calculated, the set is cleared, while the set length remains unchanged. The method for obtaining the fluctuation error factor is as follows: In the formula, This represents the fluctuation error factor of the u-th fetal heart rate data. This represents the value of the u-th fetal heart rate. This represents the u-th heart rate data value of the mother, and B represents the number of heart rate data collections. This represents the value of the i-th fetal heart rate. This represents the value of the i-th heart rate data of the parturient; the method for obtaining the abnormal factor is as follows: In the formula, This indicates the abnormal factor in the u-th heart rate data of the parturient. This represents the value of the u-th heart rate data of the mother during labor. This represents the (u-1)th heart rate data value of the mother; the method for obtaining the abnormality parameter is as follows: In the formula, A parameter indicating the degree of abnormality of the u-th fetal heart rate data. This represents the fluctuation error factor of the u-th fetal heart rate data. The confidence factor represents the confidence factor for the u-th fetal heart rate data. This represents the uth abnormal factor in the mother's heart rate data.

2. The data analysis-based nursing optimization system for delivery rooms and operating rooms according to claim 1, characterized in that, The method for collecting maternal and fetal heart rate data and storing the heart rate data in maternal and fetal heart rate arrays respectively to obtain continuous fetal and maternal heart rate data is as follows: A fetal heart rate monitor and a heart rate monitor are set up, and the fetal and maternal heart rates are collected simultaneously using the fetal heart rate monitor and the heart rate monitor respectively. The collection time interval is P seconds, and the number of collections is B. The collected fetal and maternal heart rates are stored in the fetal heart rate array and the maternal heart rate array respectively according to the collection sequence to obtain continuous fetal and maternal heart rate data.

3. The data analysis-based nursing optimization system for delivery rooms and operating rooms according to claim 1, characterized in that, The process involves continuing to collect maternal and fetal heart rate data and updating the arrays. A threshold for the degree of fetal heart rate data abnormality is set. Based on this threshold, the collected fetal heart rate data is assessed for abnormality, and medical staff are alerted to provide nursing intervention. The specific method is as follows: Simultaneously, a fetal heart rate monitor and a heart rate monitor are used to collect new fetal and maternal heart rates. The collection time interval is P seconds, and the number of collections is V. Each time, maternal and fetal data is collected, and the fetal and maternal heart rate arrays are updated. The first element in both arrays is deleted, and all remaining elements are shifted one position forward. Finally, the newly collected fetal and maternal heart rate data are added to the end of both arrays. The degree of fetal heart rate data abnormality parameter is calculated based on the new arrays, and a threshold Q is set. The abnormality parameter is compared with the threshold Q. If the abnormality parameter exceeds the threshold Q, medical staff are alerted to provide intervention.

4. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the data analysis-based delivery room and operating room care optimization system as described in any one of claims 1 to 3.

5. A computer device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the data analysis-based delivery room and operating room care optimization system as described in any one of claims 1 to 3.

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